- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Abstract and Applied Analysis
Volume 2013 (2013), Article ID 268639, 15 pages
A Real-Valued Negative Selection Algorithm Based on Grid for Anomaly Detection
College of Computer Science, Sichuan University, Chengdu 610065, China
Received 15 March 2013; Accepted 13 May 2013
Academic Editor: Fuding Xie
Copyright © 2013 Ruirui Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- D. Dasgupta, S. Yu, and F. Nino, “Recent advances in artificial immune systems: models and applications,” Applied Soft Computing Journal, vol. 11, no. 2, pp. 1574–1587, 2011.
- P. Bretscher and M. Cohn, “A theory of self-nonself discrimination,” Science, vol. 169, no. 3950, pp. 1042–1049, 1970.
- F. Burnet, The Clonal Selection Theory of Acquired Immunity, Vanderbilt University Press, Nashville, Tenn, USA, 1959.
- N. K. Jerne, “Towards a network theory of the immune system,” Annals of Immunology, vol. 125, no. 1-2, pp. 373–389, 1974.
- P. Matzinger, “The danger model: a renewed sense of self,” Science, vol. 296, no. 5566, pp. 301–305, 2002.
- M. L. Kapsenberg, “Dendritic-cell control of pathogen-driven T-cell polarization,” Nature Reviews Immunology, vol. 3, no. 12, pp. 984–993, 2003.
- S. Forrest, L. Allen, A. S. Perelson, and R. Cherukuri, “Self-nonself discrimination in a computer,” in Proceedings of the IEEE Symposium on Research in Security and Privacy, pp. 202–212, May 1994.
- T. Li, Computer Immunology, House of Electronics Industry, Beijing, China, 2004.
- T. Li, “Dynamic detection for computer virus based on immune system,” Science in China F, vol. 51, no. 10, pp. 1475–1486, 2008.
- T. Li, “An immunity based network security risk estimation,” Science in China F, vol. 48, no. 5, pp. 557–578, 2005.
- F. A. González and D. Dasgupta, “Anomaly detection using real-valued negative selection,” Genetic Programming and Evolvable Machines, vol. 4, no. 4, pp. 383–403, 2003.
- Z. Ji, Negative selection algorithms: from the thymus to V-detector [Ph.D. dissertation], University of Memphis, Memphis, Tenn, USA, 2006.
- Z. Ji and D. Dasgupta, “V-detector: an efficient negative selection algorithm with “probably adequate” detector coverage,” Information Science, vol. 19, no. 9, pp. 1390–1406, 2009.
- X. Z. Gao, S. J. Ovaska, and X. Wang, “Genetic algorithms-based detector generation in negative selection algorithm,” in Proceedings of the IEEE Mountain Workshop on Adaptive and Learning Systems (SMCals '06), pp. 133–137, July 2006.
- X. Z. Gao, S. J. Ovaska, X. Wang, and M.-Y. Chow, “Clonal optimization of negative selection algorithm with applications in motor fault detection,” in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC '06), pp. 5118–5123, Taipei, Taiwan, October 2006.
- J. M. Shapiro, G. B. Lament, and G. L. Peterson, “An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '05), pp. 337–344, Washington, DC, USA, June 2005.
- M. Ostaszewski, F. Seredynski, and P. Bouvry, “Immune anomaly detection enhanced with evolutionary paradigms,” in Proceedings of the 8th Annual Genetic and Evolutionary Computation Conference (GECCO '06), pp. 119–126, Seattle, Wash, USA, July 2006.
- T. Stibor, P. Mohr, and J. Timmis, “Is negative selection appropriate for anomaly detection?” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '05), pp. 569–576, IEEE Computer Society Press, June 2005.
- W. Chen, X. Liu, T. Li, Y. Shi, X. Zheng, and H. Zhao, “A negative selection algorithm based on hierarchical clustering of self set and its application in anomaly detection,” International Journal of Computational Intelligence Systems, vol. 4, no. 4, pp. 410–419, 2011.
- “UCI Dataset,” http://archive.ics.uci.edu/ml/datasets.
- G. Chang and J. Shi, Mathematical Analysis Tutorial, Higher Education Press, Beijing, China, 2003.
- F. Gonzalez, D. Dasgupta, and J. Gomez, “The effect of binary matching rules in negative selection,” in Proceedings of the Genetic and Evolutionary Computation (GECCO '03), pp. 196–206, Springer, Berlin, Germany, 2003.
- T. Stibor, J. Timmis, and C. Eckert, “On the appropriateness of negative selection defined over hamming shape-space as a network intrusion detection system,” in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '05), pp. 995–1002, September 2005.